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ERA5-HEAT: a global gridded historical dataset of human thermal comfort indices from climate reanalysis

Di Napoli, C., Barnard, C., Prudhomme, C., Cloke, H. L. and Pappenberger, F. (2021) ERA5-HEAT: a global gridded historical dataset of human thermal comfort indices from climate reanalysis. Geoscience Data Journal, 8 (1). pp. 2-10. ISSN 2049-6060

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To link to this item DOI: 10.1002/gdj3.102


The mean radiant temperature (MRT) and the universal thermal climate index (UTCI) are widely used as human biometeorology parameters to assess the linkages between outdoor environment and human well-being. Historically computed from meteorological station measurements, we here present ERA5-HEAT (Human thErmAl comforT), the first historical dataset of MRT and UTCI as spatially gridded records at the global scale. Derived using climate variables from ERA5, a quality-controlled reanalysis produced by the European Centre from Medium-Range Weather Forecasts (ECMWF) within the Copernicus Climate Change Service (C3S), ERA5-HEAT consists of hourly gridded maps of MRT and UTCI at 0.25°x 0.25° spatial resolution. It currently spans from 1979 to present and it will be extended in time as updates of ERA5 are made available. ERA5-HEAT provides two streams, a consolidated and an intermediate one, that are released at 2 or 3 months and 5 days behind real time, respectively. Data are publicly and freely available for download at the Climate Data Store which has been developed as part of C3S. Being the only existing global historical gridded time series of MRT and UTCI to date, ERA5-HEAT is aimed at a wide range of end users, from scientists to policy makers, with an interest in environment-health applications at any spatial and temporal scale.

Item Type:Article
Divisions:Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Life Sciences > School of Agriculture, Policy and Development > Department of Agri-Food Economics & Marketing
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:91423


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